---
title: "Dashboard"
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
    vertical_layout: fill
    source: embed
---

```{r}
library(tidyverse)
library(p8105.datasets)
library(plotly)
library(flexdashboard)
```

```{r}
data("ny_noaa")
```


```{r}
noaa_df = ny_noaa %>%
  janitor::clean_names() %>% 
  separate(col = date, into = c('year','month','day'), sep = "-" , convert = TRUE) %>%
  mutate (tmax = as.numeric(tmax),
          tmin = as.numeric(tmin),
          prcp = as.numeric(prcp),
          year = as.integer(year),
          month = as.integer(month),
          day = as.integer(day)) %>% 
  mutate(tmax = tmax/10, tmin = tmin/10, prcp = prcp/10)

target = noaa_df %>% 
  filter(year %in% 1990:1999,
         month %in% c(12,1,2)) %>% 
  sample_n(8000) %>%
  drop_na()
```

Column {data-width=650}
-----------------------------------------------------------------------

### Chart A

```{r}
target %>%
  mutate(text_label = str_c("Month:", month, "\nDay ", day)) %>% 
  plot_ly(
    x = ~tmin, y = ~tmax, type = "scatter", mode = "markers",
    color = ~year, text = ~text_label, alpha = 0.5)
```

Column {data-width=350}
-----------------------------------------------------------------------

### Chart B

```{r}
target %>% 
  mutate(year = as.factor(year)) %>% 
  plot_ly(y = ~ tmin, x = ~ year, color = ~ year, text = ~ year, type = "box", colors = "viridis")
```

### Chart C

```{r}
target %>% 
  mutate(year = as.factor(year)) %>% 
  group_by(year)%>%
  summarise(average_prcp=mean(prcp))%>%
  plot_ly(x=~year, y=~average_prcp, type="bar", color = ~year,colors = "viridis")
```